VISUALISATION AND ANALYSIS

Transcription

1 VISUALISATION AND ANALYSIS CHALLENGES FOR WALLABY Christopher Fluke David Barnes, Amr Hassan [ Scientific Computing & Visualisation Group ] CRICOSProductions provider 00111D Swinburne Astronomy

2 WALLABY Workflow Observe field Model fitting Add candidate to catalogue Ready for WALLABY science Generate spectral cube Transfer to archive Source finding

3 Visualisation + Analysis Likely data cube 6144 x 6144 spatial pixels 16,384 spectral channels ~600 gigavoxels 2.5 TB Several Petabytes of data products Existing solutions may not cope What tools does WALLABY need above/beyond what ASKAP project will provide? New software? New hardware?

4 The WALLABY Data Deluge Grand Challenges for Visualisation and Analysis A. Handling Big Data Files B. Global Views versus Image Slices C. Source Finding and Confirmation D. Desktop Visualisation and Analysis E. Data Product Management Need to understand the computing context [Assumes that all we get from ASKAP is spectral cubes] See Fluke, Barnes & Hassan (2010) e-science Challenges in Astronomy and Astrophysics Part of IEEE e-science 2010 Conference

5 Desktop Computing Today (2010) 2.5 TB Assumptions: Theoretical peak, single precision 100% efficiency using all cores/streams

6 Per-Node HPC Performance Today (2010) 2.5 TB 160 x WALLABY-sized data on 2010 desktop and HPC is worrying

7 The Multi-Core Corner (Barsdell et al. 2010) Many-core GPU Low-cost streaming co-processor Multi-core CPU Single-core CPU

8 Desktop Computing for WALLABY Assumptions: Theoretical peak, single precision 100% efficiency using all cores/streams

9 Per-Node HPC Performance for WALLABY (Specs for Low cost HPC cluster not DIRP) Bandwidth and memory are bigger factors than FLOPs

10 A. Handling Big = 2.5 TB Data Files (in 2014) HPC cluster with 72 GB per node = 36 nodes (c.f. 160) But Sufficient compute capacity in CPUs? 10 GB/GPU = 256 GPUs Remote service mode (Amr Hassan talk) Need software that supports Distributed memory architecture Data parallel algorithms FITS? NetCDF? HDF5? On the fly transforms?

11 B. Global Views versus Image Slices HI detection Visualisation: Amr Hassan Data courtesy: Russell Jurek (ATNF) LMC 5 GPUs vs 100s of CPUS GPS (Interference) Milky Way Processing artifacts 1721x1721x1024= GB x 1721 x 1024 = 12GB

12 C. Source Finding and Confirmation Identifying and extracting candidate sources Source finding is easy, right? Examine each voxel in turn, identify source contribution But every voxel contains both source and non-source WALLABY outcomes rely on source finding software that: Maximises reliablity (only extract HI sources) Completeness (finds every source in the cube) Ideal: 1:1 reliability 100% completeness

13 Computing requirements for source finders Consider using more than one source finder Tuned for different types of sources? Requires (at minimum) distributed computing approach But with GPUs Massive processing gain at much lower cost than CPU-only cluster Other source finding alternatives that are not practical with CPU? (Brute force on GPU) Accelerate elements of other source finders?

14 D. Desktop Visualisation and Analysis Main memory (bandwidth) is biggest limitation 16 GB (= 3 min to load) Cropping or subsampling (qualitative only) Calculate min, max, mean? Seconds (best case) Extra calculations? Standard desktop will not have sufficient compute capability Add a GPU? Not a drastic improvement (2-3 GB RAM) Perhaps x10 at best

15 Desktop 3D Volume Rendering Hardware-accelerated, texture-based, 3D volume rendering Today: Standard (NVIDIA GT120 GPU with 512 MB RAM) vox at 6-10 fps for 600x600 pixel output Top-end (ATI Radeon 5970) vox at 8-15 fps on 1000x1000 output Tomorrow: 2 GB (500 megavoxel ~ voxels) for GPU Likely to be 4 fps?

16 Demonstration 3D texture rendering (on a laptop) NGC3198 (courtesy E. de Blok/THINGS) Original: 1024 x 1024 x 72 (293 MB) Scaled: 512 x 512 x 72 (18 MB)

17 E. Data Product Management Solutions over and above ASKAP databases/archives Need to understand specific requirements for WALLABY Can t use text files for 0.5 million sources! (c.f. HIPASS) Options Build our own system? Buy a solution don t reinvent it? Look to SDSS, WiggleZ, Millennium and see what they did? Important to think about future scalability

18 Visualisation and Analysis of WALLABY Data Will require evolutionary and revolutionary changes in hardware and software More processing steps will move from desktop to HPC remote services GPUs show great potential

19 Potential solutions